Optimized Selection of Wetland Water Quality Monitoring Points Based on Information Entropy and Fuzzy Similarity

  • Xinjian Xiang
Part of the The International Federation for Information Processing book series (IFIPAICT, volume 259)

Known as the kidney of earth, wetland has significant ecological functions such as freshwater conservation, poison elimination, carbon storage, water quality purification, flood storage and drought control, climate regulation and remaining biodiversity etc. So protecting wetland is protecting ourselves. Water environment quality best reflects the ecological environment condition of wetland. According to multi-index and Spatial and Temporal variation of wetland water pollution, combining optimized selection requirements of wetland water quality monitoring, fuzzy similarity is propose. Through constructing multi-index monitoring data samples Decision-making Matrix, fuzzy similarity matrix between sample data and their mean values is established. According to the index value variation, the index weights are calculated based on information entropy theory. With the index weight and sample fuzzy similarity matrix, comprehensive fuzzy similarity of each monitoring point is calculated. Finally, according to comprehensive fuzzy similarity, each monitoring point is reasonably clustered, then representative points is selected from each category, so distribution optimization could be realized. Practical running proves that this scheme is simple and feasible, and extensionally applied to optimize other environmental monitoring points.


fuzzy similarity method information entropy wetland water quality monitoring optimized selection 


  1. Jiang Peng, Survey on key technology of WSN-based wetland water quality remote real time monitoring system [J]. Chinese journal of sensors and actuators No. 1, 2007, pp. 83-86.Google Scholar
  2. Liang weizhen, ye jinglun. Water quality evaluation based on optimal fuzzy clustering [J]. The Administration and Technique of Environmental Monitoring No. 6, 2002, pp. 6-7.Google Scholar
  3. Sun Shimin, Shi Haixing, Evaluation of Milking Machine Based on Entropy Technology and Idea l Point Principle [J]. Transactions of the Chinese Society for Agricultural Machinery, No. 5, 2007, pp. 82-87.Google Scholar
  4. XiangXinjian, A method to sensor data fusion based on fuzzy and statistics integration Chinese journal of sensors and actuators, No. 2, 2004, pp. 197-199.Google Scholar
  5. Xu lizhong, Zhang jiangshang. Optimization of atmospheric environmental monitoring sites with modified intimate value method [J]. Environmental Engineering No. 18, 2002, pp. 50-53.Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Xinjian Xiang
    • 1
  1. 1.College of Automation & Electrical EngineeringZhejiang University of Science and TechnologyChina

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